[PDF] Top 20 Learning Multilingual Word Embeddings Using Image Text Data
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Learning Multilingual Word Embeddings Using Image Text Data
... on learning multilingual word embeddings, in which semantically similar words within and across lan- guages have similar word embeddings (Ruder, ...2017). Multilingual ... See full document
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GlobalTrait: Personality Alignment of Multilingual Word Embeddings
... CNN using multilingual embeddings plus the GlobalTrait aligned embeddings In both ‘-multi’ and ‘-GlobalTrait’, models, the training set includes both the English and the source language’s ... See full document
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Multilingual Training of Crosslingual Word Embeddings
... bilingual word embeddings. Our multilingual word embeddings, on the other hand, map both Italian and Spanish to the same space without using any direct bilingual signal between ... See full document
11
Learning Multilingual Word Embeddings in Latent Metric Space: A Geometric Approach
... bilingual lexicon induction, in which a direct dictionary between the source and target languages is not available. The semi-supervised extension of our algorithm shows that our framework can leverage unlabeled ... See full document
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Deep neural model with enhanced embeddings for pharmaceutical and chemical entities recognition in Spanish clinical text
... concept embeddings and analyze why its performance is lower than the medi- cal word ...train word embeddings obtained from mul- tiple multilingual biomedical corpus to obtain ... See full document
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Aligning Multilingual Word Embeddings for Cross Modal Retrieval Task
... shared multilingual text encoder by adapting the align- ment between languages for image-description re- trieval task while ...of word embeddings in multiple ...multimodal ... See full document
7
Deep Multilingual Correlation for Improved Word Embeddings
... the word and bi- gram similarity ...original word vector results, the best-tuned CCA setting (CCA-1), the en- semble of the top-3 CCA settings (CCA-Ens), and the same for DCCA (with both tuning ...when ... See full document
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Joint Learning of Sense and Word Embeddings
... the embeddings to represent the ...train data portion of each dataset, and measure the classifi- cation accuracy using the corresponding test data ...better word embeddings not ... See full document
7
On Learning Word Embeddings From Linguistically Augmented Text Corpora
... the word similarity task, the embeddings were trained on a smaller section of English Wikipedia corpus (Al-Rfou et ...specific embeddings using a corpus extracted from APTnotes, a repository ... See full document
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Beyond Bilingual: Multi sense Word Embeddings using Multilingual Context
... Word embeddings, which represent a word as a point in a vector space, have become ubiquitous to several NLP ...a word, by ex- ploiting crosslingual signals to aid sense ...multi-sense ... See full document
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Comparing Pretrained Multilingual Word Embeddings on an Ontology Alignment Task
... Word embeddings constitute a distributed word representa- tion to leverage the semantics of words by mapping them to vectors of real numbers, where each dimension of the embedding represents a latent ... See full document
7
Learning bilingual word embeddings with (almost) no bilingual data
... bilingual embeddings without any bilingual ...language embeddings into the target language, a decoder that reconstructs the origi- nal embeddings, and a discriminator that distin- guishes mapped ... See full document
12
Dict2vec : Learning Word Embeddings using Lexical Dictionaries
... Learning word embeddings on large unla- beled corpus has been shown to be suc- cessful in improving many natural lan- guage ...resentations using additional external data. Resulting ... See full document
10
Learning Word Embeddings for Data Sparse and Sentiment Rich Data Sets
... insufficient data to completely train a word embedding. The SUD data set con- sists of a few hundred people and only a fraction of these are active (Firth et ...small data set of text ... See full document
8
Sparse Coding of Neural Word Embeddings for Multilingual Sequence Labeling
... for learning distributed word represen- tations for various specific language analysis ...train word representations on large amounts of unan- notated texts from Wikipedia, then update the pre- ... See full document
16
Towards Incremental Learning of Word Embeddings Using Context Informativeness
... new word acquisition by an adult speaker who already masters a substantial vocab- ...large text corpus. A novel word is then learnt by using information present in its con- text ... See full document
7
Online Learning of Interpretable Word Embeddings
... for word representation, denoted as non-negative sparse embedding (NNSE) (Mur- phy et ...interpretable word embeddings by applying non-negative con- straints for word ...learns word ... See full document
6
Learning Unsupervised Multilingual Word Embeddings with Incremental Multilingual Hubs
... Monolingual embeddings are provided, based on the CBOW model trained on the WaCKy corpora for English, Italian and German (Baroni et ...1,993 word pairs for each language ...3,660 word pairs. We rely ... See full document
13
Multilingual Models for Compositional Distributed Semantics
... for learning multilingual word embeddings using parallel data in conjunction with a multilingual ob- jective function for compositional vector ...to multilingual ... See full document
11
Joint learning of frequency and word embeddings for multilingual readability assessment
... selecting learning material for children of differ- ent grade levels, for language learners, for com- prehension tests, skills training, text summarisa- tion, simplification systems and so ...a ... See full document
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